Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.
时间: 2023-12-12 16:19:13 浏览: 33
This error occurs when you try to call the `numpy()` method on a PyTorch tensor that requires gradient computation. To fix this, you can use the `detach()` method to create a new tensor that does not require gradient computation and then call the `numpy()` method on the detached tensor. Here's an example:
```
import torch
# create a tensor and set requires_grad=True
x = torch.ones(2, 2, requires_grad=True)
# perform some operations on the tensor
y = x + 2
z = y * y * 3
out = z.mean()
# call the numpy() method on the tensor
# this will raise an error
# np_array = out.numpy()
# detach the tensor and call the numpy() method on the detached tensor
np_array = out.detach().numpy()
print(np_array)
```
In this example, we create a tensor `x` with `requires_grad=True`, perform some operations on it, and compute a scalar value `out`. When we try to call the `numpy()` method on `out`, we get the error message. To fix this, we detach `out` using the `detach()` method and then call the `numpy()` method on the detached tensor.